CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
TileBars: visualization of term distribution information in full text information access
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The Journal of Machine Learning Research
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Semiology of graphics
Jigsaw: Supporting Investigative Analysis through Interactive Visualization
VAST '07 Proceedings of the 2007 IEEE Symposium on Visual Analytics Science and Technology
Studying the history of ideas using topic models
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Topic Significance Ranking of LDA Generative Models
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
The automatic creation of literature abstracts
IBM Journal of Research and Development
Seriation and matrix reordering methods: An historical overview
Statistical Analysis and Data Mining
MatLink: enhanced matrix visualization for analyzing social networks
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction - Volume Part II
Evaluating topic models for digital libraries
Proceedings of the 10th annual joint conference on Digital libraries
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Optimizing semantic coherence in topic models
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Interpretation and trust: designing model-driven visualizations for text analysis
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Docuburst: visualizing document content using language structure
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
A graph-based topic extraction method enabling simple interactive customization
Proceedings of the 2013 ACM symposium on Document engineering
Crowd synthesis: extracting categories and clusters from complex data
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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Topic models aid analysis of text corpora by identifying latent topics based on co-occurring words. Real-world deployments of topic models, however, often require intensive expert verification and model refinement. In this paper we present Termite, a visual analysis tool for assessing topic model quality. Termite uses a tabular layout to promote comparison of terms both within and across latent topics. We contribute a novel saliency measure for selecting relevant terms and a seriation algorithm that both reveals clustering structure and promotes the legibility of related terms. In a series of examples, we demonstrate how Termite allows analysts to identify coherent and significant themes.